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environments such as low light, heat haze, and adverse weather is significantly difficult. These conditions not only degrade video quality but also complicate interpretation by humans and machines, making post
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), and selected World Tour one-week stage races. Data sources will include race videos, rider power and speed data, and race commentary to codify key race events, using expert knowledge and available
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best practice guidance. You should have demonstrable skills in qualitative data analysis, including familiarity with, or knowledge of, engaging research methods (e.g. participatory video, photovoice
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Physical Layer Security Additional enhanced training: Leadership (CMI Level 7), Innovation, Public engagement, Hackathons and more Video: www.youtube.com/watch?v=Gdqa5ykrrdg Hear from one of our students
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interest in biodiversity, functional ecology, image/video analysis, and conservation. Experience with programming, statistical analysis, or spatial modelling is desirable but not essential, as full training
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interest in biodiversity, functional ecology, image/video analysis, and conservation. Experience with programming, statistical analysis, or spatial modelling is desirable but not essential, as full training
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, LLMs), 2) define and model dimensions related to the perception of animacy when interacting with objects and people using videos (behaviour, fMRI, and MEG), 3) determine to what extent these brain
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engagement, Hackathons and more Video: www.youtube.com/watch?v=Gdqa5ykrrdg Hear from one of our students: Fully Funded PhD with FORT CDT As global reliance on secure digital systems grows, your research will
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will include race videos, rider power and speed data, and race commentary to codify key race events, using expert knowledge and available evidence. - Develop a post-race analysis framework, process, and
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– such as tandem neural networks , video diffusion models , and reinforcement learning – will be explored to efficiently navigate these high-dimensional, nonlinear design spaces. To achieve robust property